Research on Surface Defect Detection Technology of Wind Turbine Blade Based on UAV Image

Abstract

In the background of “double carbon,” vigorously developing new energy is particularly important. Wind power is an important clean energy source. In the field of new energy, wind power scale is also expanding. With the wind turbine, the probability of large-scale blade damage is also increasing. Because the large wind turbine blade crack detection cost is high and because of the poor working environment, this paper proposes a wind turbine blade surface defect detection method based on UAV acquisition images and digital image processing. The application of weighted averages to achieve grayscale processing, followed by median filtering to achieve image noise reduction, and an improved histogram equalization algorithm is proposed and used for the characteristics of the UAV acquisition images, which enhances the image by limiting the contrast adaptive histogram equalization algorithm to make the details at the target area and defects more clear and complete, and improves the detection efficiency. The detection of the blade surface is achieved by separating and extracting the feature information from the defects through image foreground segmentation, threshold processing, and framing by the connected domain. The validity and accuracy of the proposed method in leaf detection were verified by experiments.